Discovery of a Potent and Selective Tyrosine Kinase 2 Inhibitor: TAK-279.

TYK2 is a key mediator of IL12, IL23, and type I interferon signaling, and these cytokines have been implicated in the pathogenesis of multiple inflammatory and autoimmune diseases such as psoriasis, rheumatoid arthritis, lupus, and inflammatory bowel diseases. Supported by compelling data from human genome-wide association studies and clinical results, TYK2 inhibition through small molecules is an attractive therapeutic strategy to treat these diseases. Herein, we report the discovery of a series of highly selective pseudokinase (Janus homology 2, JH2) domain inhibitors of TYK2 enzymatic activity. A computationally enabled design strategy, including the use of FEP+, was instrumental in identifying a pyrazolo-pyrimidine core. We highlight the utility of computational physics-based predictions used to optimize this series of molecules to identify the development candidate 30, a potent, exquisitely selective cellular TYK2 inhibitor that is currently in Phase 2 clinical trials for the treatment of psoriasis and psoriatic arthritis.

Reliable and Accurate Solution to the Induced Fit Docking Problem for Protein-Ligand Binding.

We present a reliable and accurate solution to the induced fit docking problem for protein-ligand binding by combining ligand-based pharmacophore docking, rigid receptor docking, and protein structure prediction with explicit solvent molecular dynamics simulations. This novel methodology in detailed retrospective and prospective testing succeeded to determine protein-ligand binding modes with a root-mean-square deviation within 2.5 Å in over 90% of cross-docking cases. We further demonstrate these predicted ligand-receptor structures were sufficiently accurate to prospectively enable predictive structure-based drug discovery for challenging targets, substantially expanding the domain of applicability for such methods.

Investigation of the proteolytic functions of an expanded cercarial elastase gene family in Schistosoma mansoni.

BACKGROUND: Cercarial elastase is the major invasive larval protease in Schistosoma mansoni, a parasitic blood fluke, and is essential for host skin invasion. Genome sequence analysis reveals a greatly expanded family of cercarial elastase gene isoforms in Schistosoma mansoni. This expansion appears to be unique to S. mansoni, and it is unknown whether gene duplication has led to divergent protease function. METHODS: Profiling of transcript and protein expression patterns reveals that cercarial elastase isoforms are similarly expressed throughout the S. mansoni life cycle. Computational modeling predicts key differences in the substrate-binding pockets of various cercarial elastase isoforms, suggesting a diversification of substrate preferences compared with the ancestral gene of the family. In addition, active site labeling of SmCE reveals that it is activated prior to exit of the parasite from its intermediate snail host. CONCLUSIONS: The expansion of the cercarial gene family in S. mansoni is likely to be an example of gene dosage. In addition to its critical role in human skin penetration, data presented here suggests a novel role for the protease in egress from the intermediate snail host. This study demonstrates how enzyme activity-based analysis complements genomic and proteomic studies, and is key in elucidating proteolytic function.

Predicting and improving the membrane permeability of peptidic small molecules.

We evaluate experimentally and computationally the membrane permeability of matched sets of peptidic small molecules bearing natural or bioisosteric unnatural amino acids. We find that the intentional introduction of hydrogen bond acceptor-donor pairs in such molecules can improve membrane permeability while retaining or improving other favorable drug-like properties. We employ an all-atom force field based method to calculate changes in free energy associated with the transfer of the peptidic molecules from water to membrane. This computational method correctly predicts rank order experimental permeability trends within congeneric series and is much more predictive than calculations (e.g., clogP) that do not consider three-dimensional conformation.

Insight through molecular mechanics Poisson-Boltzmann surface area calculations into the binding affinity of triclosan and three analogues for FabI, the E. coli enoyl reductase.

Keeping pace with emerging drug resistance in clinically important pathogens will be greatly aided by inexpensive yet reliable computational methods that predict the binding affinities of ligands for drug targets. We present results using the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method to calculate the affinity of a series of triclosan analogues for the E. coli enoyl reductase FabI, spanning a 450000-fold range of binding affinities. Significantly, a high correlation is observed between the calculated binding energies and those determined experimentally. Further examination indicates that the van der Waals energies are the most correlated component of the total affinity (r2 = 0.74), indicating that the shape of the inhibitor is very important in defining the binding energies for this system. The validation of MM-PBSA for the E coli FabI system serves as a platform for inhibitor design efforts focused on the homologous enzyme in Staphylococcus aureus and Mycobacterium tuberculosis.